Dalal Anuj K, Plombon Savanna, Konieczny Kaitlyn, Motta-Calderon Daniel, Malik Maria, Garber Alison, Lam Alyssa, Piniella Nicholas, Leeson Marie, Garabedian Pamela, Goyal Abhishek, Roulier Stephanie, Yoon Cathy, Fiskio Julie M, Schnock Kumiko O, Rozenblum Ronen, Griffin Jacqueline, Schnipper Jeffrey L, Lipsitz Stuart, Bates David W
Department of Medicine, Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
Harvard Medical School, Boston, Massachusetts, USA.
BMJ Qual Saf. 2025 May 19;34(6):377-388. doi: 10.1136/bmjqs-2024-017183.
Adverse event surveillance approaches underestimate the prevalence of harmful diagnostic errors (DEs) related to hospital care.
We conducted a single-centre, retrospective cohort study of a stratified sample of patients hospitalised on general medicine using four criteria: transfer to intensive care unit (ICU), death within 90 days, complex clinical events, and none of the aforementioned high-risk criteria. Cases in higher-risk subgroups were over-sampled in predefined percentages. Each case was reviewed by two adjudicators trained to judge the likelihood of DE using the Safer Dx instrument; characterise harm, preventability and severity; and identify associated process failures using the Diagnostic Error Evaluation and Research Taxonomy modified for acute care. Cases with discrepancies or uncertainty about DE or impact were reviewed by an expert panel. We used descriptive statistics to report population estimates of harmful, preventable and severely harmful DEs by demographic variables based on the weighted sample, and characteristics of harmful DEs. Multivariable models were used to adjust association of process failures with harmful DEs.
Of 9147 eligible cases, 675 were randomly sampled within each subgroup: 100% of ICU transfers, 38.5% of deaths within 90 days, 7% of cases with complex clinical events and 2.4% of cases without high-risk criteria. Based on the weighted sample, the population estimates of harmful, preventable and severely harmful DEs were 7.2% (95% CI 4.66 to 9.80), 6.1% (95% CI 3.79 to 8.50) and 1.1% (95% CI 0.55 to 1.68), respectively. Harmful DEs were frequently characterised as delays (61.9%). Severely harmful DEs were frequent in high-risk cases (55.1%). In multivariable models, process failures in assessment, diagnostic testing, subspecialty consultation, patient experience, and history were significantly associated with harmful DEs.
We estimate that a harmful DE occurred in 1 of every 14 patients hospitalised on general medicine, the majority of which were preventable. Our findings underscore the need for novel approaches for adverse DE surveillance.
不良事件监测方法低估了与医院护理相关的有害诊断错误（DEs）的发生率。
我们对内科住院患者的分层样本进行了一项单中心回顾性队列研究，采用四个标准：转入重症监护病房（ICU）、90天内死亡、复杂临床事件以及无上述高风险标准。高风险亚组中的病例按预定百分比进行过度抽样。每个病例由两名经过培训的裁决者进行审查，他们使用更安全的诊断工具来判断诊断错误的可能性；描述危害、可预防性和严重程度；并使用为急性护理修改的诊断错误评估和研究分类法识别相关的流程故障。对诊断错误或影响存在差异或不确定性的病例由专家小组进行审查。我们使用描述性统计方法，根据加权样本报告按人口统计学变量对有害、可预防和严重有害诊断错误的总体估计，以及有害诊断错误的特征。使用多变量模型调整流程故障与有害诊断错误之间的关联。
在9147例符合条件的病例中，每个亚组随机抽取675例：100%的ICU转入患者、38.5%的90天内死亡患者、7%的有复杂临床事件的患者以及2.4%的无高风险标准的患者。根据加权样本，有害、可预防和严重有害诊断错误的总体估计分别为7.2%（95%CI 4.66至9.80）、6.1%（95%CI 3.79至8.50）和1.1%（95%CI 0.55至1.68）。有害诊断错误通常表现为延迟（61.9%）。严重有害诊断错误在高风险病例中很常见（55.1%）。在多变量模型中，评估、诊断测试、专科会诊、患者体验和病史方面的流程故障与有害诊断错误显著相关。
我们估计，在内科住院的每14名患者中就有1人发生有害诊断错误，其中大多数是可预防的。我们的研究结果强调了采用新方法进行不良诊断错误监测的必要性。
